COVID-19 Report Group Project

Introduction

COVID-19 is a sudden global pandemic that has affected the lives of people around the world, including us. Thus we’re looking at one of the most important things that’s happening in the world, looking at this outbreak from a data point of view. Each of our group members will focus on one particular problem related to COVID-19 and analyze datasets corresponding to our topics, namely: quarantine, vaccine development, transportation and unemployment.

Summary Information

• We all know quarantine is an essential part of COVID-19 and everyone has experienced quarantine as a demand from countries’ government. In the future analysis of COVID-19 quarantine in this project, we will be focusing on the quarantine level required by the government of 185 countries. The latest quarantine requirements are updated on 2021-11-21. In our dataset, we can see the latest quarantine level by the US government made on 2021-11-16 is level 1 which indicates the government recommend not leaving house.

• After the outbreak of COVID-19, the development of vaccines has been one of the top concerns. There are now several types of vaccines available, and it is highly recommended to take COVID vaccine before we go somewhere else to protect ourselves. Now the global vaccination rate is 0.46, which counts the ratio of the number of people who got at least one shot.

• Transportation was seriously influenced by COVID-19 since 2020. This project will focus on how the number of trips made by residents in U.S is impacted. From the data, if ignore the distances of trips, the average number of trips by residents per day in 2019is 1352383954, and the average population staying at home in 2019 is 63388644. The average number of trips by residents per day in 2020 is 1002128303, and the average population staying at home in 2020 is 81237730. The numbers of trips within 10 miles and more than 10 miles have decreased from 704303279 and 306663519 in 2019 to 522491647 and 229377608 in 2020. And obviously, the number of population staying at home increased while the number of trips decreased dramatically, which means more people choose to stay at home and reduced the number of trips due to COVID-19.

• It is clear that employment and workforce is one area that has been severely impacted due to the outbreak of COVID. From the overall statistics of countries and regions from 1991 to 2020, we could compute the overall range of the change in unemployment rates of all countries and regions listed in the dataset. Out of the 235 countries/regions in the dataset, all of them (235) experiences an increase in the unemployment rate. For the United States, there is a increase of 5.96% in unemployment rates. We can also identify the country/region with highest and lowest increase in unemployment rates, which are Belarus and North Korea respectively.

Aggregate Table

Here is a table that shows the accumulated number of people that got at least one shot of COVID vaccine and the ratio of the number of people getting vaccinated in each country in descending order. This can also help us to see which country is much safer to travel to. The existing types of vaccine are not 100% effective at preventing infection, but as more people got vaccinated, the risk of getting COVID-19 will be reduced.

Country	Total Number of People Vaccinated	Population	Vaccinatoin Rate
Gibraltar	43572	33691	1.29
Bhutan	850260	779900	1.09
Brunei	406147	441532	0.92
Cuba	10417429	11317498	0.92
United Arab Emirates	9234032	9991083	0.92
Niue	1467	1614	0.91
Falkland Islands	3182	3528	0.90
Portugal	9078016	10167923	0.89
Cayman Islands	58566	66498	0.88
Chile	16948566	19212362	0.88
Singapore	4753131	5453600	0.87
Cambodia	14180132	16946446	0.84
Seychelles	83455	98910	0.84
Malta	428457	516100	0.83
South Korea	42788375	51305184	0.83
Iceland	281457	343360	0.82
Spain	38511766	46745211	0.82
Argentina	36868777	45605823	0.81
Canada	30942901	38067913	0.81
Uruguay	2777953	3485152	0.80
Denmark	4609606	5813302	0.79
Italy	47510120	60367471	0.79
Japan	99967315	126050796	0.79
Malaysia	25863879	32776195	0.79
Australia	20172618	25788217	0.78
Finland	4312640	5548361	0.78
Ireland	3870440	4982904	0.78
Norway	4250593	5465629	0.78
Qatar	2286675	2930524	0.78
Brazil	164909492	213993441	0.77
Ecuador	13719508	17888474	0.77
France	52163110	67564251	0.77
Isle of Man	65781	85410	0.77
Netherlands	13225520	17173094	0.77
New Zealand	3938572	5122600	0.77
Taiwan	18353379	23855008	0.77
Tokelau	1048	1368	0.77
Belgium	8857802	11632334	0.76
Costa Rica	3897970	5139053	0.76
Turks and Caicos Islands	29774	39226	0.76
Bermuda	46877	62092	0.75
Colombia	38224618	51265841	0.75
San Marino	25400	34010	0.75
Sweden	7661178	10160159	0.75
Vietnam	73712293	98168829	0.75
Kuwait	3200433	4328553	0.74
Sri Lanka	15997924	21497306	0.74
Faeroe Islands	35966	49053	0.73
Maldives	398563	543620	0.73
Nauru	7929	10873	0.73
Saint Helena	4477	6095	0.73
United Kingdom	49459244	68207114	0.73
Andorra	55613	77354	0.72
Fiji	654299	902899	0.72
Germany	60176232	83900471	0.72
Mauritius	914682	1273428	0.72
United States	238355405	332915074	0.72
Austria	6433224	9043072	0.71
Luxembourg	448987	634814	0.71
Thailand	49493343	69950844	0.71
Turkmenistan	4342520	6117933	0.71
Cyprus	626805	896005	0.70
Lithuania	1888141	2689862	0.70
Anguilla	10501	15125	0.69
Greece	7189661	10370747	0.69
Israel	6454890	9291000	0.69
Latvia	1287191	1866934	0.69
Panama	3017947	4381583	0.69
El Salvador	4443450	6518500	0.68
Iran	57796260	85028760	0.68
Macao	448847	658391	0.68
Mongolia	2264019	3329282	0.68
Peru	22850911	33359415	0.68
Switzerland	5886207	8715494	0.68
Tonga	72199	106759	0.68
Aruba	71646	107195	0.67
Bahrain	1171475	1748295	0.67
Greenland	37851	56868	0.67
Liechtenstein	25814	38254	0.67
Samoa	133872	200144	0.67
Antigua and Barbuda	64110	98728	0.65
Nicaragua	4298221	6702379	0.64
Czechia	6721079	10724553	0.63
Dominican Republic	6902976	10953714	0.63
Estonia	832944	1325188	0.63
Hong Kong	4795891	7552800	0.63
Hungary	6040455	9634162	0.63
New Caledonia	180172	288217	0.63
Oman	3265946	5223376	0.63
Turkey	53959223	85042736	0.63
Mexico	79039262	130262220	0.61
Morocco	22423711	37344787	0.60
Slovenia	1234287	2078723	0.59
India	808251701	1393409033	0.58
French Polynesia	162199	282534	0.57
Belize	228734	404915	0.56
Cook Islands	9865	17572	0.56
Poland	21082467	37797000	0.56
Venezuela	16096132	28704947	0.56
Barbados	156324	287708	0.54
Croatia	2210090	4081657	0.54
Curacao	89120	164796	0.54
Cape Verde	299671	561901	0.53
Saint Kitts and Nevis	28256	53546	0.53
Uzbekistan	18016644	33935765	0.53
Indonesia	144010344	276361788	0.52
Tunisia	6217068	11935764	0.52
Guyana	403322	790329	0.51
Azerbaijan	5117014	10223344	0.50
Bonaire Sint Eustatius and Saba	13340	26445	0.50
Laos	3654112	7379358	0.50
Trinidad and Tobago	696166	1403374	0.50
Wallis and Futuna	5548	11094	0.50
Kiribati	59715	121388	0.49
Slovakia	2682797	5460726	0.49
Serbia	3275745	6871547	0.48
Timor	651742	1343875	0.48
Monaco	18379	39520	0.47
Paraguay	3407320	7219641	0.47
Russia	68733892	145912022	0.47
Rwanda	6229115	13276517	0.47
Kazakhstan	8813588	18994958	0.46
Honduras	4566230	10062994	0.45
Bolivia	5157113	11832936	0.44
Montenegro	279039	628051	0.44
Suriname	260207	591798	0.44
Bangladesh	71008251	166303494	0.43
China	614544255	1444216102	0.43
Guernsey	27068	63385	0.43
North Macedonia	880253	2082661	0.42
Dominica	29516	72172	0.41
Jersey	41271	101073	0.41
Jordan	4209767	10269022	0.41
Belarus	3730648	9442867	0.40
Romania	7731353	19127772	0.40
Bahamas	153917	396914	0.39
Botswana	945406	2397240	0.39
Sao Tome and Principe	86498	223364	0.39
Albania	1085174	2872934	0.38
Pakistan	82781587	225199929	0.37
Grenada	40489	113015	0.36
Palestine	1893288	5222756	0.36
Philippines	39443074	111046910	0.36
Guatemala	6159183	18249868	0.34
Nepal	10127260	29674920	0.34
Montserrat	1646	4981	0.33
Tuvalu	3829	11925	0.32
Ukraine	13959469	43466822	0.32
Comoros	271917	888456	0.31
Georgia	1236349	3979773	0.31
Tajikistan	3010286	9749625	0.31
Myanmar	16520085	54806014	0.30
Saint Lucia	55258	184401	0.30
South Africa	18064219	60041996	0.30
Vanuatu	95111	314464	0.30
Lesotho	621467	2159067	0.29
Sint Maarten (Dutch part)	12474	43421	0.29
Armenia	822387	2968128	0.28
Lebanon	1916028	6769151	0.28
Egypt	27053785	104258327	0.26
Eswatini	305574	1172369	0.26
Saudi Arabia	9170360	35340680	0.26
Zimbabwe	3900668	15092171	0.26
Bosnia and Herzegovina	810663	3263459	0.25
Bulgaria	1753291	6896655	0.25
Libya	1758105	6958538	0.25
British Virgin Islands	7129	30423	0.23
Jamaica	693996	2973462	0.23
Mauritania	1086572	4775110	0.23
Moldova	937464	4024025	0.23
Solomon Islands	157876	703995	0.22
Mozambique	6766872	32163045	0.21
Saint Vincent and the Grenadines	23355	111269	0.21
Angola	6782697	33933611	0.20
Iraq	7746182	41179351	0.19
Guinea-Bissau	355781	2015490	0.18
Equatorial Guinea	242667	1449891	0.17
Kyrgyzstan	1150653	6628347	0.17
Algeria	6752140	44616626	0.15
Namibia	373337	2587344	0.14
Togo	1211167	8478242	0.14
Uganda	6190526	47123533	0.13
Guinea	1650940	13497237	0.12
Afghanistan	4353540	39835428	0.11
Cote d’Ivoire	3057144	27053629	0.11
Gambia	239967	2486937	0.10
Congo	526217	5657017	0.09
Kenya	5110419	54985702	0.09
Liberia	472426	5180208	0.09
Sierra Leone	739006	8141343	0.09
Benin	973188	12451031	0.08
Central African Republic	374641	4919987	0.08
Gabon	180656	2278829	0.08
Ghana	2676298	31732128	0.08
Senegal	1339634	17196308	0.08
Djibouti	71297	1002197	0.07
Ethiopia	8412098	117876226	0.07
Malawi	1203466	19647681	0.06
Sudan	2687769	44909351	0.06
Somalia	740749	16359500	0.05
Syria	890862	18275704	0.05
Mali	795626	20855724	0.04
Zambia	784521	18920657	0.04
Cameroon	787359	27224262	0.03
Nigeria	7243317	211400704	0.03
Papua New Guinea	263880	9119005	0.03
Burkina Faso	433088	21497097	0.02
Madagascar	565886	28427333	0.02
Niger	507176	25130810	0.02
South Sudan	212037	11381377	0.02
Tanzania	1486104	61498438	0.02
Yemen	545259	30490639	0.02
Chad	189271	16914985	0.01
Haiti	111866	11541683	0.01
Burundi	2072	12255429	0.00
Democratic Republic of Congo	154900	92377986	0.00
Pitcairn	0	47	0.00

Chart1

• In order to know the relationship between COVID-19 and quarantine, we have to check the quarantine level required by the government during a tension period of COVID-19 in each country. In this chart we will see a map shows the quarantine level of 185 countries on the day that the US had the highest new cases, which is Jan.8,2021. Let’s see what’s the quarantine level required by the US government and other countries on Jan.8,2021. This map might tell us how acquiring quarantine affect the new cases.

• There are four levels of stay_home_requirements measured for countries:

  • 0 - No measures

  • 1 - recommend not leaving house

  • 2 - require not leaving house with exceptions for daily exercise, grocery shopping, and ‘essential’ trips

  • 3 - Require not leaving house with minimal exceptions (e.g. allowed to leave only once every few days, or only one person can leave at a time, etc.)

• In the map below, we can see the stay_home_requirements for the US is Level 2 on Jan.08.2021 which implies the government require not leaving house with exceptions for daily exercise, grocery shopping, and ‘essential’ trips. Thus we can see the US government was trying to eliminate outdoor activities as much as possible when we have the highest cases. We also can see countries like China and Pakistan required Level 3 quarantine which only allows minimal exception of leaving house, this can reveal more when we relate this map with COVID-19 new cases data on Jan.08.2021.You can interact with the map below.

Chart2

In order to investigate the influences on numbers of trips by residents brought by epidemic, we need to compare the patterns before and after the spread of COVID-19. The data involves in this plot is divided into tow two groups, data for 2019 form 2019-01-01 to 2019-12-21 and data fro 2020 from 2020-01-31 to 2020-12-31, where as data of 2019 represents pattern before COVID-19 and data 2020 represents patterns during COVID-19. Form the plot, it is obvious to notice that the number of trips, ignore the distances of trips, by residents started to decreases after the February, which the beginning of COVID-19 and finally led to a great difference on patterns between 2020 and 2019. This data presents that more people tends to travel less after spread of COVID-19.

Chart3

In this line chart of several selected countries/regions and their unemployment rate from the year 2010 to 2020, we can see generally decreasing trends of most countries/regions throughout the years 2010 to 2019, with the exception of South Africa and Latin America & Caribbean. However, it is clearly observable that all countries and regions, whether or not they are in a decreasing trend of unemployment, has taken a sharp rise during the year 2019 to 2020 due to the outbreak of COVID19. Some of the most sharp turns we can identify include the United States, Latin America & Caribbean, and South Asia.